Determining rotational orientation of a deep brain stimulation electrode in a three-dimensional image

ABSTRACT

Disclosed is a computer-implemented medical data processing method for determining an orientation of an electrode, the electrode being configured for electrically stimulating an anatomical structure of a patient and comprising a rotational orientation marker, the method comprising executing, on at least one processor of at least one computer, steps of: a) acquiring (S 1.1 ), at the at least one processor, rotational image data describing two-dimensional medical images of the anatomical structure and the electrode, the two-dimensional medical images having been taken with a two-dimensional medical imaging apparatus during rotation of the medical imaging apparatus relative to the anatomical structure, the rotational image data further describing, for each of the two-dimensional medical images, an imaging perspective relative to the anatomical structure associated with the respective two-dimensional medical image; b) determining (S 1.2 ), by the at least one processor and based on the rotational image data, rotational orientation data describing the rotational orientation of the electrode in the reference system of the two-dimensional medical images; c) acquiring (S 1.3 ), at the at least one processor, tomographic image data describing a set of tomographic medical images of the anatomical structure; d) determining (S 1.4 ), by the at least one processor and based on the rotational image data and the tomographic image data and the rotational orientation data, electrode orientation data describing a rotational orientation of the electrode in a reference system of the tomographic medical image data.

The present invention relates to a computer-implemented medical methodfor determining an orientation of an electrode. The electrode is forexample configured for electrically (for example, electromagnetically)stimulating an anatomical structure of a patient and comprises arotational orientation marker: The invention also relates to a computerconfigured to execute a program corresponding to the method and amedical system for determining an orientation of an electrode comprisingsuch a computer.

TECHNICAL BACKGROUND

Directional Deep Brain Stimulation (DBS) leads (also called electrodes)allow for focusing the stimulation towards certain angles of the lead(i.e. electrode). For planning the stimulation or evaluating stimulationeffects the knowledge of the correct directional orientation of the leadwith respect to the patient anatomy is necessary. The lead is equippedwith a rotationally asymmetric marker which was designed to be detectedand evaluated by post-operative imaging. Unfortunately, MRI is noteligible due to metal in the leads and CTs are too blurry in order torecognize the marker with sufficient accuracy.

All previous methods do not allow for an automatized, traceable andaccurate measurement of the rotational angle defining the rotationalangular orientation of the electrode around its longitudinal axis.

The present invention is designed to provide a reliable method fordetermining the orientation of an electrode in the reference system of athree-dimensional medical image.

Aspects of the present invention, examples and exemplary steps and theirembodiments are disclosed in the following. Different exemplary featuresof the invention can be combined in accordance with the inventionwherever technically expedient and feasible.

EXEMPLARY SHORT DESCRIPTION OF THE PRESENT INVENTION

In the following, a short description of the specific features of thepresent invention is given which shall not be understood to limit theinvention only to the features or a combination of the featuresdescribed in this section.

The disclosed method uses rotational x-rays (e.g. from rotationalangiography, cone beam CT, C-arm x-ray). On the series of x-ray shotstaken while the detector rotates around the head, the lead (electrode)and its marker is clearly visible on the images from different angles.These images allow for determining the angle of the marker with respectto the image plane and/or the reference system of the images. In orderto transfer this knowledge into 3D (three-dimensional) patient system,the 2D x-ray images are registered to an anatomical 3D image volume withthe help of an automatic algorithm. By means of blending digitallyreconstructed radiographs of the 3d image data onto the 2D x-ray imagesthe user can verify the match of 2D and 3D images immediately and assessthe accuracy of the calculated orientation angle. Also, the rotationalorientation of the lead in the reference system of the 3D image volumecan be determined.

GENERAL DESCRIPTION OF THE PRESENT INVENTION

In this section, a description of the general features of the presentinvention is given for example by referring to possible embodiments ofthe invention.

In general, the invention reaches the aforementioned object byproviding, in a first aspect, a computer-implemented medical method fordetermining an orientation of an electrode. The electrode is for exampleconfigured for electrically (for example, electromagnetically)stimulating an anatomical structure of a patient and comprises arotational orientation marker.

The electrode may be a directional electrode for deep brain stimulation(a DBS electrode) which comprises different distinct contacts which arelocated in discrete segments along the longitudinal axis of theelectrode and may take the form of a patch not extending entirely aroundthe circumference of the electrode but extending only along an angularsector (a ring segment) around the longitudinal axis of the electrode.The electrode generally takes an elongate, basically cylindrical and inone example rigid shape having a distal end pointing towards theinterior of a patient's body and a proximal end pointing towards anexterior of a patient's body. Due to its elongation, the electrode isdefined to have a longitudinal axis extending e.g. from proximal end tothe distal end of the electrode. The electrode is generally adirectional DBS electrode which allows for selective stimulation of onlya three-dimensional angular sector in the direction of the respectivecontact. In order to achieve a desired stimulation of an anatomicalstructure being or comprising a target region which shall be stimulated,the rotational angular orientation of the directional electrode relativeto the position of the anatomical structure (target region) has to bedetermined so that the anatomical structure (target region) lies in thesector covered by the directional characteristic (emissioncharacteristic) of at least one of the directional contacts of theelectrode.

The method according to the first aspect is concerned with determiningthe angular orientation of the electrode for example relative to a planein which it is depicted in a two-dimensional medical image, in order todetermine, on the basis of further information as explained below, therotational orientation of the electrode relative to the anatomicalstructure, for example in a reference system of a three-dimensionalimage data set depicting both the anatomical structure and theelectrode. The angular orientation can be defined as a rotational phaseof the electrode (for example, of the orientation marker) in the medicaltwo-dimensional image around a rotational axis defined by the extensionof the longitudinal axis of the electrode, for example as a rotationalphase of the depicted planar section through the electrode in the imageplane of the two-dimensional image relative to the circumferentialposition of the directional marker on the circumference of theelectrode. In other words, the angular orientation is defined as arotation angle along the circumference of the electrode relative to e.g.the position of the orientation marker on the circumference. In evenother words, the angular orientation is defined by the angle (forexample, spatial angle, which may be defined in a three-dimensionalreference system such as spherical coordinates) between a plane in whichat least one of a predetermined (for example, at least one of known orfixed) position of the orientation marker (for example, of its firstpart) or a radius of the electrode intersecting that position, and thelongitudinal axis of the electrode lie on the one hand, and the imageplane of the two-dimensional medical image on the other hand. Theorientations of those two planes are generally parallel to one anotherand/or both orientations lie in a common plane. Minor three-dimensionaldeviations from this spatial relationship between the orientations canbe neglected for achieving the effect of the method according to thefirst aspect. The spatial relationship between the predeterminedposition of the orientation marker and the remainder of the electrode ispredetermined (for example, at least one of known or fixed), for examplefrom electrode template data comprising constructional data describing(for example, defining or representing) the geometry of the electrode. Acoordinate transformation between the reference system in which theangular orientation is defined and a coordinate system in which at leastone of the remainder of the electrode or the image positions in thetwo-dimensional medical image are defined is predetermined (for example,at least one of known or fixed). Within the meaning of this disclosure,the term reference system encompasses and generally is equivalent to theterm coordinate system. Thus, the rotational orientation of theelectrode in the reference system of the two-dimensional medical image(in which positions defining the image contents of the two-dimensionalmedical image are defined) can be determined from analysing thetwo-dimensional medical image.

Notably, placement of such an electrode in the human or animal body isnot part of the disclosed method. Furthermore, execution of thedisclosed method does not require the electrode to be placed while thedisclosed method is executed. In other words, the disclosed methodaccording to the first aspect is a method of at least one of operatingor controlling a data processing device such as a computer, e.g. byrunning a corresponding program on the data processing device so as tocause the data processing device to execute the steps of the methodaccording to the first aspect.

The method according to the first aspect is for example a dataprocessing method. The method according to the first aspect comprisesexecuting, on at least one processor of at least one computer (forexample at least one computer being part of a deep brain stimulationcalibration or tuning system), the following exemplary steps which areexecuted by the at least one processor.

In a (for example first) exemplary step, rotational image data isacquired which describes (for example, at least one of defines orrepresents) two-dimensional medical images of (i.e. depicting orshowing) the anatomical structure and the electrode. Specifically, thetwo-dimensional images (for example each) depict both the anatomicalstructure and the electrode. Generally, the anatomical structure may beany anatomical body part containing at least one nerve fibre which maybe electrically (electromagnetically) stimulated (e.g. the anatomicalstructure comprises, for example is, at least part of the brain), ormuscular tissue which may be electrically stimulated to cause e.g.muscular contraction or extension.

The two-dimensional medical images have been or are being taken with atwo-dimensional medical imaging apparatus or method such as imaging witha C-arm (C-arm x-ray, also called C-arm radiography), by rotationalangiography or cone beam computed x-ray tomography (cone beam CT). Forexample, the two-dimensional images have been or are being taken duringrotation of the medical imaging apparatus relative to the anatomicalstructure, i.e. each two-dimensional image has been taken at a differentrotational position of the medical imaging apparatus relative to theposition of the anatomical structure and the electrode, for example suchthat immediately subsequent positions of the medical imaging apparatusare associated with two-dimensional images taken immediatelysubsequently in the order of their generation. For example, eachtwo-dimensional medical image is associated with a different imagingperspective (for example, relative to the position of the anatomicalstructure). The rotational image data further describes, for each of thetwo-dimensional medical images, an imaging perspective relative to theanatomical structure associated with the respective two-dimensionalmedical image. The imaging perspective is preferably defines by theposition of the medical imaging apparatus which the medical imagingapparatus had relative to the anatomical structure and for example theelectrode when the respective two-dimensional image was generated. Thestep of generating the rotational image data (i.e. conducting theassociated imaging procedure) generally is not part of the claimedmethod and is in one example performed before the method according tothe first aspect is executed. The rotational image data is then acquired(read) by the method at a later point in time. However, generation ofthe rotational image data may in another example of the method be partof the method according to the first aspect.

In a further (for example second) exemplary step, rotational orientationdata is determined which describes (for example defines or represents)the rotational orientation of the electrode in the reference system ofthe two-dimensional medical images (in which positions defining theimage contents of the rotational image data are defined). The referencesystem of the two-dimensional images is for example a reference systemused for generating the rotational image data and may be predeterminedby the two-dimensional medical imaging apparatus (such as C-arm x-raydevice). The rotational orientation data is determined for example basedon the rotational image data, for example from the image depiction ofthe electrode in the respective two-dimensional image. To this end, atleast one of the two-dimensional medical images is analysed concerningthe image appearance of the orientation marker in the two-dimensionalimage. In one example, all of the two-dimensional medical images areaccordingly analysed. This can be done for example by determining, basedon the rotational image data, an image appearance of the orientationmarker, for example by at least one of:

-   -   segmenting an image appearance of the electrode in the at least        one or each of the two-dimensional medical images;    -   edge detection of constituents of the at least one or each of        the two-dimensional medical images;    -   comparing the image appearance of the electrode in the at least        one or each of the two-dimensional medical images to previously        acquired and predetermined electrode template data describing        constructional data of the electrode (such as at least one of        its geometry and the spatial relationship—at least one of        position and orientation—between at least one directional        contact and the orientation marker).

The rotational orientation of the electrode is then determined fromknowledge about the imaging perspective associated with the respectivetwo-dimensional image in the reference system of the two-dimensionalmedical images, and for example the previously acquired electrodetemplate data, if necessary considering any recalculation of positionsor orientations of part of the electrode or spatial relationshipsdescribed by the electrode template data into the reference system ofthe two-dimensional images.

In a further example, the for example second exemplary step comprisesacquiring predetermined orientation data which describes (for exampledefines or represents) a predetermined rotational orientation of theelectrode in the reference system of the two-dimensional medical images.The position and orientation of the orientation marker relative to theelectrode is predetermined (for example, at least one of known or fixed)for example and included in or derivable from the electrode templatedata which to that end may be acquired by the method according to thefirst aspect. The predetermined orientation may for example anorientation in which the orientation marker has a predetermined (forexample, at least one of known or fixed) appearance in a two-dimensionalimage. For example, the orientation marker has a first part which coversa circumferential surface along less than 180° of the circumference andfor a predetermined (for example, at least one of known or fixed) length(and in a more specific example less than the total length) along thelongitudinal axis of the electrode, and for the remaining circumference.In one example, the orientation marker has, at a further position alongthe longitudinal axis, a further, second part which covers the surfaceof the electrode at least over the remainder of the circumference). Theorientation of the electrode is generally determined by extracting, fromthe at least one of the two-dimensional medical images, an imageappearance of the orientation marker, and comparing it to apredetermined (for example, at least one of known or fixed) imageappearance of the orientation marker. For example, the first part has apredetermined thickness if it is two-dimensionally imaged in a specificimaging plane, for example in a plane intersecting both the longitudinalaxis of the electrode and representing a mirror plane of symmetry of theorientation marker. This thickness of the image appearance of the firstpart may define the predetermined orientation of the orientation markerand the electrode. The method then determines, based on the rotationalorientation data and the predetermined orientation data, optimalorientation data.

The optimal orientation data describes (for example, defines orrepresents) the two-dimensional medical image associated with arotational orientation of the electrode (in the image plane of thetwo-dimensional medical image) fulfilling a predetermined condition inrelation to the predetermined rotational orientation. Within thisdisclosure, that two-dimensional medical image is also called theoptimal two-dimensional medical image, specifically because it isassociated with the so-called optimal rotational orientation of theorientation marker when compared to the predetermined orientation. Theoptimal two-dimensional image is determined for example by comparing theimage appearance of the orientation marker in the at least one of thetwo-dimensional medical images (for example, in each one of thetwo-dimensional medical images) to the predetermined image appearance ofthe orientation marker in order to determine whether the imageappearance of the orientation marker fulfils a predetermined conditionrelative to the predetermined image appearance, for example whether itsthickness in the at least one two-dimensional medical image is at leastwithin a predetermined (for example, at least one of known or fixed)limit equal to its predetermined thickness. If it is determined that theimage appearance of the orientation marker in the at least one of thetwo-dimensional medical image fulfils the predetermined condition, theassociated two-dimensional medical image is determined to be the optimaltwo-dimensional medical image. If more than one of the two-dimensionalmedical images is analysed in this manner, and if better fulfilment ofthe predetermined condition is determined for another one of thetwo-dimensional medical images, then that other two-dimensional medicalimage is determined to be the optimal two-dimensional medical image.

In a (for example third) exemplary step, tomographic image data isacquired which describes (for example, defines or represents) a set oftomographic medical images of the anatomical structure. The positionsdefining the image contents of the tomographic image data are defined inthree dimensions (i.e. in a three-dimensional reference system), and thetomographic image data is for example generated before execution of themethod according to the first aspect starts. For example, it may bepresent in the form of a planning image data set used for planning anenvisaged medical procedure. The tomographic image data allows forgeneration of slice images of the anatomical structure from differentperspectives including the perspective associated with the optimaltwo-dimensional medical image. The tomographic image data may begenerated by at least one of computational x-ray tomography, medicalresonance imaging, ultrasound imaging, positron emission tomography,medical resonance diffusion tensor imaging or reconstructing athree-dimensional image volume from the rotational image data.

In a (for example fourth) exemplary step, electrode orientation data isdetermined which describes a rotational orientation of the electrode ina reference system of the tomographic medical image data (is defined.The electrode orientation data is determined based on the rotationalimage data and the tomographic image data and the rotational orientationdata. For example, the rotational orientation of the electrode in thereference system of the optimal two-dimensional medical image (in whichpositions defining the image contents of the rotational image data aredefined) is transformed into the reference system of the tomographicimage data (in which positions defining the image contents of thetomographic image data are defined). Such a transformation ispredetermined (for example, at least one of known or fixed) and is basedon the predetermined (at least one of known or fixed) spatialrelationship between the two reference systems. The transformation isfor example a linear transformation and may be embodied by a matrixmultiplication, and may be for example a transformation of bases betweenthe two reference systems.

The method may in one example include steps of determining the positionand orientation of the electrode in the reference system of thetomographic image data and determining whether the anatomical structureis covered by the directional characteristic of a predetermined contactof the electrode, i.e. by an electric field for electrically stimulatingthe anatomical structure having for example a predetermined fieldstrength and spatial relationship relative to at least one of theposition of the directional contact and the position of the anatomicalstructure. To that end, also the electrode template data comprisingconstructional data describing the predetermined (for example, at leastone of known or fixed) geometry of the electrode (specifically, thespatial relationship between the orientation marker and the desireddirectional contact) may be acquired by the method and serve as basisfor determining a spatial relationship between the directional contactand the position of the anatomical structure. The position of theanatomical structure may be defined by the geometric or physical centreof gravity of the anatomical structure. The method may then alsodetermine the percentage of the whole volume of the anatomical structurecovered by the electric field and whether this percentage is within adesired range for performing electric stimulation of the anatomicalstructure.

The method according to the first aspect for example comprises a step ofdetermining projected image data. The projected image data is determinedbased on (for example, from) the tomographic medical image data anddescribes (for example defines or represents) a projected tomographicmedical image which is generated (e.g. synthesized) from the tomographicimage data from the imaging perspective (for example relative to theanatomical structure, specifically the position of the anatomicalstructure) associated with the optimal two-dimensional medical image. Inother words, the projected tomographic medical image describes (forexample shows or depicts) the anatomical structure at least within apredetermined limit (e.g. accuracy limit in the same (i.e. at least to apredetermined extent similar) appearance as the optimal two-dimensionalmedical image. The projected image data is for example determined bydetermining a transformation, for example a positional transformation,between a reference system of the the rotational image data (in whichpositions defining the image contents of the rotational image data aredefined) defined and the reference system of the tomographic image data(in which positions defining the image contents of the tomographic imagedata are defined), and the electrode orientation data is then determinedby applying the transformation to the rotational orientation describedby the rotational orientation data. Such a transformation ispredetermined (for example, at least one of known or fixed) and is basedon the predetermined (at least one of known or fixed) spatialrelationship between the two reference systems. The transformation isfor example a linear transformation and may be embodied by a matrixmultiplication, and may be for example a transformation of bases betweenthe two reference systems.

Then, the method may comprise a step of determining projectedorientation data. The projected orientation data describes (for example,defines or represents) the rotational orientation of the electrode inthe reference system of the projected medical image. The projectedorientation data is determined based on the projected image data and therotational image data and the rotational orientation data, for exampleby transforming the previously determined rotational orientation of theelectrode from the reference system of the two-dimensional medical image(in which positions defining the image contents of the rotational imagedata are defined) into to the reference system of the projectedtomographic medical image (in which positions defining the imagecontents of the projected tomographic medical image are defined). Such atransformation is predetermined (for example, at least one of known orfixed) and is based on the predetermined (at least one of known orfixed) spatial relationship between the two reference systems. Thetransformation is for example a linear transformation and may beembodied by a matrix multiplication, and may be for example atransformation of bases between the two reference systems. Because theimaging perspective associated with the projected tomographic image isknown, it is possible to transform the rotational orientation of theelectrode in the projected tomographic image into the rotationalorientation of the electrode in the entire set of tomographic medicalimages so that, for example in conjunction with known information aboutthe geometry of the electrode, the orientation and for example alsoposition of the electrode in the reference system of the tomographicimage data can be determined. Therefore, the method according to thefirst aspect for example determines the electrode orientation data basedon the projected orientation data and the projected image data.

In one example, the projected image data is determined for all imagingperspectives with which the series of two-dimensional medical images isassociated, and the projected image data describes a projectedtomographic medical image for each of the imaging perspectives, andwherein the projected orientation data is determined based on theprojected tomographic medical image best matching the optimaltwo-dimensional image, which match is determined for example by at leastone of:

-   -   comparing colour values (for example, grey values) between the        optimal two-dimensional medical image and the projected        tomographic medical images; then, for example, a correlation of        the colour values may be established between the two images,        possibly taking into account the spatial relationships of        neighbouring image elements (such as pixels or voxels) and their        associated colour values;    -   applying a fusion algorithm (an image fusion algorithm, for        example a rigid or elastic fusion algorithm) to register the        optimal two-dimensional medical image to each one of the        projected tomographic medical images and selecting, from the        projected tomographic medical images and for determining the        projected orientation data, only the projected tomographic        medical image associated with the best fusion result. The best        fusion result can be defined by a metric calculated by the        fusion algorithm which indicates a best correspondence between        the data sets (for example, between geometric features such as        image contents by comparing the correspondence between spatial        relationships of constituents of the image contents of one image        relative to one another on the one hand to spatial relationships        of constituents of the image contents of another image relative        to one another on the other hand).

In an example of the method according to the first aspect, therotational image data and the tomographic image data have been generatedby application of an x-ray-based imaging modality, for example therotational image data has been generated applying rotationalconventional x-ray imaging, for example rotational radiography, and thetomographic image data has been generated by applying computed x-raytomography. Specifically, the correspondence between colour values (e.g.grey values) defining the image contents of the rotational image dataand colour values (e.g. grey values) defining the image contents of thetomographic image data is predetermined (for example, at least one ofknown and fixed) and may be used as an input to the method according tothe first aspect. Such a correspondence is generally known from thephysics of x-ray absorption for certain materials such as biologicaltissue forming e.g. the anatomical structure.

In another example of the method according to the first aspect, therotational image data has been generated by application of anx-ray-based imaging modality and the tomographic image data has beengenerated by applying an imaging modality not involving application ofx-rays, for example the rotational image data has been generatedapplying rotational conventional x-ray imaging (such as in the precedingexample) and the tomographic image data has been generated by applyingmagnetic resonance imaging or positron emission imaging (PET) or anultrasound imaging (sonography) or magnetic resonance diffusion tensorimaging (MR-DTI). In order to make the colour values (e.g. grey values)defining the image contents of the rotational image data comparable tothe colour values (e.g. grey values) defining the image contents of thetomographic image data comparable, a mapping between the two differentcolour value scales associated with the rotational image data and thetomographic image data, respectively, may in one example be input to themethod. Such a mapping may be included in atlas data describing amulti-modal atlas of the anatomical structure.

In this example, the method may therefore comprise the following steps:

-   -   acquiring atlas data describing a model (for example, an        image-based model) of the anatomical structure and information        about an image appearance of the anatomical structure in the        imaging modality not involving application of x-rays and in the        x-ray-based tomographic imaging modality (defined for example by        colour values such as grey values defining the image        constituents corresponding to the anatomical structure in both        modalities), wherein the x-ray-based imaging modality is for        example computed x-ray tomography;    -   determining, based on the tomographic image data and the atlas        data, transformed appearance data describing an image appearance        of the anatomical structure in the x-ray-based tomographic        imaging modality (defined for example by colour values such as        grey values defining the image constituents corresponding to the        anatomical structure in the x-ray-based tomographic imaging        modality).

The electrode orientation data may then be determined further based onthe transformed appearance data and for example the projected image datamay then be determined further based on (for example, from) thetransformed appearance data.

The atlas data may describe a multimodal atlas of the anatomicalstructure in which models of the anatomical body parts are stored whichhave been generated with each a different imaging modality, and atransformation rule between anatomically corresponding parts of themodels. That allows for a transformation of the tomographic image datainto an imaging modality which is different from the one which was usedfor its generation, for example to make the medical image datacomparable to that different imaging modality. The transformation rulemay be based on tissue class information stored for each model whichdescribes the image appearance (e.g. colour value such as a multi-colourvalue or a greyscale value) of the constituents of the anatomical bodypart in the respective imaging modality.

Furthermore, the atlas data may have been generated from medical imagesof the anatomical structure of a plurality of patients. Alternatively,the atlas data may have been generated from at least one medical imageof the anatomical structure of only the specific patient for whom therotational image data and the tomographic image data was generated, i.e.the model may be part of a patient-specific atlas.

The atlas data comprises for example positional information defined in athree-dimensional coordinate system (representing the reference systemused for defining positional information contained in the atlas data).For example, the atlas data has been generated from tomographic imagesof the anatomical structure.

The transformed appearance data may be determined by matching the atlasdata with the tomographic image data, for example by determining atransformation, for example a positional transformation, between areference system of the tomographic image data (in which positionsdefining the image contents of the tomographic image data are defined)and a reference system of the atlas data (in which positions definingthe image contents of the atlas data are defined) or by conducting forexample a colour value match (such as grey value match) between thetomographic image data and the atlas data. The positional transformationmay be predetermined (for example, at least one of known or fixed) orestablished as part of the method according to the first aspect forexample by applying a fusion algorithm (such as a rigid or elasticfusion algorithm (to the tomographic image data and the atlas data).

In one example of the method according to the first aspect, theelectrode comprises at least two directional contacts which are spacedapart from another, and wherein an image appearance of at least part ofeach of at least two spaces in between the at least two directionalcontacts in the two-dimensional medical images is used to verify therotational orientation described by the rotational orientation data.

In a second aspect, the invention is directed to a computer programwhich, when running on at least one processor (for example, a processor)of at least one computer (for example, a computer) or when loaded intoat least one memory (for example, a memory) of at least one computer(for example, a computer), causes the at least one computer to performthe above-described method according to the first aspect.

In a third aspect, the invention is directed to a non-transitorycomputer-readable program storage medium on which the program accordingto the second aspect is stored.

In a fourth aspect, the invention is directed to at least one computer(for example, a computer), comprising at least one processor (forexample, a processor) and at least one memory (for example, a memory),wherein the program according to the second aspect is running on theprocessor or is loaded into the memory, or wherein the at least onecomputer is operably coupled to the program storage medium according tothe third aspect for executing the program stored on the program storagemedium.

In a fifth aspect, the invention is directed to a (physical, for exampleelectrical, for example technically generated) signal wave, for examplea digital signal wave, carrying information which represents the programaccording to the second aspect.

In a sixth aspect, the invention is directed a medical system fordetermining an orientation of an electrode, the electrode beingconfigured for electrically stimulating an anatomical structure of apatient and comprising a rotational orientation marker, the systemcomprising:

-   a) the at least one computer according to the preceding claim; and-   b) at least one electronic data storage device storing at least one    of the rotational image data or the tomographic image data or, as    far as applicable, the atlas data,    -   wherein the at least one computer is operably coupled to the at        least one electronic data storage device for acquiring, from the        at least one data storage device, at least one of the rotational        image data or the tomographic image data or, as far as        applicable, the atlas data.

In an example, the system according to the sixth aspect furthercomprises the two-dimensional medical imaging apparatus, wherein thetwo-dimensional medical imaging apparatus is operably coupled to the atleast one computer for allowing the at least one computer to receive,from the two-dimensional medical imaging apparatus, at least oneelectronic signal corresponding to the rotational image data.

In general, the invention does not involve or for example comprise orencompass an invasive step which would represent a substantial physicalinterference with the body requiring professional medical expertise tobe carried out and entailing a substantial health risk even when carriedout with the required professional care and expertise. For example, theinvention does not comprise a step of irradiating the anatomical bodypart and/or the patient's body with ionizing radiation so that it doesnot comprise any steps of therapy of the human or animal body, forexample it does not comprise any step of therapy or surgery. Moreparticularly, the invention does not involve or in particular compriseor encompass any surgical or therapeutic activity. The invention isinstead directed as applicable to reading and processing data andoperating or controlling a computer to execute a program which causesthe computer to perform the data processing method according to thefirst aspect. For this reason alone, no surgical or therapeutic activityand in particular no surgical or therapeutic step is necessitated orimplied by carrying out the invention.

It is within the scope of the present invention to combine one or morefeatures of one or more embodiments or aspects of the invention in orderto form a new embodiment wherever this is technically expedient and/orfeasible. Specifically, a feature of one embodiment which has the sameor a similar function to another feature of another embodiment can beexchanged with said other feature, and a feature of one embodiment whichadds an additional function to another embodiment can for example beadded to said other embodiment.

Definitions

In this section, definitions for specific terminology used in thisdisclosure are offered which also form part of the present disclosure.

The method in accordance with the invention is for example a computerimplemented method. For example, all the steps or merely some of thesteps (i.e. less than the total number of steps) of the method inaccordance with the invention can be executed by a computer (forexample, at least one computer). An embodiment of the computerimplemented method is a use of the computer for performing a dataprocessing method. An embodiment of the computer implemented method is amethod concerning the operation of the computer such that the computeris operated to perform one, more or all steps of the method.

The computer for example comprises at least one processor and forexample at least one memory in order to (technically) process the data,for example electronically and/or optically. The processor being forexample made of a substance or composition which is a semiconductor, forexample at least partly n- and/or p-doped semiconductor, for example atleast one of II-, III-, IV-, V-, VI-semiconductor material, for example(doped) silicon and/or gallium arsenide. The calculating steps describedare for example performed by a computer. Determining steps orcalculating steps are for example steps of determining data within theframework of the technical method, for example within the framework of aprogram. A computer is for example any kind of data processing device,for example electronic data processing device. A computer can be adevice which is generally thought of as such, for example desktop PCs,notebooks, netbooks, etc., but can also be any programmable apparatus,such as for example a mobile phone or an embedded processor. A computercan for example comprise a system (network) of “sub-computers”, whereineach sub-computer represents a computer in its own right. The term“computer” includes a cloud computer, for example a cloud server. Theterm “cloud computer” includes a cloud computer system which for examplecomprises a system of at least one cloud computer and for example aplurality of operatively interconnected cloud computers such as a serverfarm. Such a cloud computer is preferably connected to a wide areanetwork such as the world wide web (WWW) and located in a so-calledcloud of computers which are all connected to the world wide web. Suchan infrastructure is used for “cloud computing”, which describescomputation, software, data access and storage services which do notrequire the end user to know the physical location and/or configurationof the computer delivering a specific service. For example, the term“cloud” is used in this respect as a metaphor for the Internet (worldwide web).

For example, the cloud provides computing infrastructure as a service(IaaS). The cloud computer can function as a virtual host for anoperating system and/or data processing application which is used toexecute the method of the invention. The cloud computer is for examplean elastic compute cloud (EC2) as provided by Amazon Web Services™. Acomputer for example comprises interfaces in order to receive or outputdata and/or perform an analogue-to-digital conversion. The data are forexample data which represent physical properties and/or which aregenerated from technical signals. The technical signals are for examplegenerated by means of (technical) detection devices (such as for exampledevices for detecting marker devices) and/or (technical) analyticaldevices (such as for example devices for performing (medical) imagingmethods), wherein the technical signals are for example electrical oroptical signals. The technical signals for example represent the datareceived or outputted by the computer. The computer is preferablyoperatively coupled to a display device which allows informationoutputted by the computer to be displayed, for example to a user. Oneexample of a display device is an augmented reality device (alsoreferred to as augmented reality glasses) which can be used as “goggles”for navigating. A specific example of such augmented reality glasses isGoogle Glass (a trademark of Google, Inc.). An augmented reality devicecan be used both to input information into the computer by userinteraction and to display information outputted by the computer.Another example of a display device would be a standard computer monitorcomprising for example a liquid crystal display operatively coupled tothe computer for receiving display control data from the computer forgenerating signals used to display image information content on thedisplay device. A specific embodiment of such a computer monitor is adigital lightbox. The monitor may also be the monitor of a portable, forexample handheld, device such as a smart phone or personal digitalassistant or digital media player.

Within the framework of the invention, computer program elements can beembodied by hardware and/or software (this includes firmware, residentsoftware, micro-code, etc.). Within the framework of the invention,computer program elements can take the form of a computer programproduct which can be embodied by a computer-usable, for examplecomputer-readable data storage medium comprising computer-usable, forexample computer-readable program instructions, “code” or a “computerprogram” embodied in said data storage medium for use on or inconnection with the instruction-executing system. Such a system can be acomputer; a computer can be a data processing device comprising meansfor executing the computer program elements and/or the program inaccordance with the invention, for example a data processing devicecomprising a digital processor (central processing unit or CPU) whichexecutes the computer program elements, and optionally a volatile memory(for example a random access memory or RAM) for storing data used forand/or produced by executing the computer program elements. Within theframework of the present invention, a computer-usable, for examplecomputer-readable data storage medium can be any data storage mediumwhich can include, store, communicate, propagate or transport theprogram for use on or in connection with the instruction-executingsystem, apparatus or device. The computer-usable, for examplecomputer-readable data storage medium can for example be, but is notlimited to, an electronic, magnetic, optical, electromagnetic, infraredor semiconductor system, apparatus or device or a medium of propagationsuch as for example the Internet. The computer-usable orcomputer-readable data storage medium could even for example be paper oranother suitable medium onto which the program is printed, since theprogram could be electronically captured, for example by opticallyscanning the paper or other suitable medium, and then compiled,interpreted or otherwise processed in a suitable manner. The datastorage medium is preferably a non-volatile data storage medium. Thecomputer program product and any software and/or hardware described hereform the various means for performing the functions of the invention inthe example embodiments. The computer and/or data processing device canfor example include a guidance information device which includes meansfor outputting guidance information. The guidance information can beoutputted, for example to a user, visually by a visual indicating means(for example, a monitor and/or a lamp) and/or acoustically by anacoustic indicating means (for example, a loudspeaker and/or a digitalspeech output device) and/or tactilely by a tactile indicating means(for example, a vibrating element or a vibration element incorporatedinto an instrument). For the purpose of this document, a computer is atechnical computer which for example comprises technical, for exampletangible components, for example mechanical and/or electroniccomponents. Any device mentioned as such in this document is a technicaland for example tangible device.

The expression “acquiring data” for example encompasses (within theframework of a computer implemented method) the scenario in which thedata are determined by the computer implemented method or program.Determining data for example encompasses measuring physical quantitiesand transforming the measured values into data, for example digitaldata, and/or computing the data by means of a computer and for examplewithin the framework of the method in accordance with the invention. Themeaning of “acquiring data” also for example encompasses the scenario inwhich the data are received or retrieved by the computer implementedmethod or program, for example from another program, a previous methodstep or a data storage medium, for example for further processing by thecomputer implemented method or program. Generation of the data to beacquired may but need not be part of the method in accordance with theinvention. The expression “acquiring data” can therefore also forexample mean waiting to receive data and/or receiving the data. Thereceived data can for example be inputted via an interface. Theexpression “acquiring data” can also mean that the computer implementedmethod or program performs steps in order to (actively) receive orretrieve the data from a data source, for instance a data storage medium(such as for example a ROM, RAM, database, hard drive, etc.), or via theinterface (for instance, from another computer or a network). The dataacquired by the disclosed method or device, respectively, may beacquired from a database located in a data storage device which isoperably to a computer for data transfer between the database and thecomputer, for example from the database to the computer. The computeracquires the data for use as an input for steps of determining data. Thedetermined data can be output again to the same or another database tobe stored for later use. The database or database used for implementingthe disclosed method can be located on network data storage device or anetwork server (for example, a cloud data storage device or a cloudserver) or a local data storage device (such as a mass storage deviceoperably connected to at least one computer executing the disclosedmethod). The data can be made “ready for use” by performing anadditional step before the acquiring step. In accordance with thisadditional step, the data are generated in order to be acquired. Thedata are for example detected or captured (for example by an analyticaldevice). Alternatively or additionally, the data are inputted inaccordance with the additional step, for instance via interfaces. Thedata generated can for example be inputted (for instance into thecomputer). In accordance with the additional step (which precedes theacquiring step), the data can also be provided by performing theadditional step of storing the data in a data storage medium (such asfor example a ROM, RAM, CD and/or hard drive), such that they are readyfor use within the framework of the method or program in accordance withthe invention. The step of “acquiring data” can therefore also involvecommanding a device to obtain and/or provide the data to be acquired. Inparticular, the acquiring step does not involve an invasive step whichwould represent a substantial physical interference with the body,requiring professional medical expertise to be carried out and entailinga substantial health risk even when carried out with the requiredprofessional care and expertise. In particular, the step of acquiringdata, for example determining data, does not involve a surgical step andin particular does not involve a step of treating a human or animal bodyusing surgery or therapy. In order to distinguish the different dataused by the present method, the data are denoted (i.e. referred to) as“XY data” and the like and are defined in terms of the information whichthey describe, which is then preferably referred to as “XY information”and the like.

In the field of medicine, imaging methods (also called imagingmodalities and/or medical imaging modalities) are used to generate imagedata (for example, two-dimensional or three-dimensional image data) ofanatomical structures (such as soft tissues, bones, organs, etc.) of thehuman body. The term “medical imaging methods” is understood to mean(advantageously apparatus-based) imaging methods (for example so-calledmedical imaging modalities and/or radiological imaging methods) such asfor instance computed tomography (CT) and cone beam computed tomography(CBCT, such as volumetric CBCT), x-ray tomography, magnetic resonancetomography (MRT or MRI), conventional x-ray, sonography and/orultrasound examinations, and positron emission tomography. For example,the medical imaging methods are performed by the analytical devices.Examples for medical imaging modalities applied by medical imagingmethods are: X-ray radiography, magnetic resonance imaging, medicalultrasonography or ultrasound, endoscopy, elastography, tactile imaging,thermography, medical photography and nuclear medicine functionalimaging techniques as positron emission tomography (PET) andSingle-photon emission computed tomography (SPECT), as mentioned byWikipedia. The image data thus generated is also termed “medical imagingdata”. Analytical devices for example are used to generate the imagedata in apparatus-based imaging methods. The imaging methods are forexample used for medical diagnostics, to analyse the anatomical body inorder to generate images which are described by the image data. Theimaging methods are also for example used to detect pathological changesin the human body. However, some of the changes in the anatomicalstructure, such as the pathological changes in the structures (tissue),may not be detectable and for example may not be visible in the imagesgenerated by the imaging methods. A tumour represents an example of achange in an anatomical structure. If the tumour grows, it may then besaid to represent an expanded anatomical structure. This expandedanatomical structure may not be detectable; for example, only a part ofthe expanded anatomical structure may be detectable. Primary/high-gradebrain tumours are for example usually visible on MRI scans when contrastagents are used to infiltrate the tumour. MRI scans represent an exampleof an imaging method. In the case of MRI scans of such brain tumours,the signal enhancement in the MRI images (due to the contrast agentsinfiltrating the tumour) is considered to represent the solid tumourmass. Thus, the tumour is detectable and for example discernible in theimage generated by the imaging method. In addition to these tumours,referred to as “enhancing” tumours, it is thought that approximately 10%of brain tumours are not discernible on a scan and are for example notvisible to a user looking at the images generated by the imaging method.

Image fusion can be elastic image fusion or rigid image fusion. In thecase of rigid image fusion, the relative position between the pixels ofa 2D image and/or voxels of a 3D image is fixed, while in the case ofelastic image fusion, the relative positions are allowed to change.

In this application, the term “image morphing” is also used as analternative to the term “elastic image fusion”, but with the samemeaning.

Elastic fusion transformations (for example, elastic image fusiontransformations) are for example designed to enable a seamlesstransition from one dataset (for example a first dataset such as forexample a first image) to another dataset (for example a second datasetsuch as for example a second image). The transformation is for exampledesigned such that one of the first and second datasets (images) isdeformed, for example in such a way that corresponding structures (forexample, corresponding image elements) are arranged at the same positionas in the other of the first and second images. The deformed(transformed) image which is transformed from one of the first andsecond images is for example as similar as possible to the other of thefirst and second images. Preferably, (numerical) optimisation algorithmsare applied in order to find the transformation which results in anoptimum degree of similarity. The degree of similarity is preferablymeasured by way of a measure of similarity (also referred to in thefollowing as a “similarity measure”). The parameters of the optimisationalgorithm are for example vectors of a deformation field. These vectorsare determined by the optimisation algorithm in such a way as to resultin an optimum degree of similarity. Thus, the optimum degree ofsimilarity represents a condition, for example a constraint, for theoptimisation algorithm. The bases of the vectors lie for example atvoxel positions of one of the first and second images which is to betransformed, and the tips of the vectors lie at the corresponding voxelpositions in the transformed image. A plurality of these vectors ispreferably provided, for instance more than twenty or a hundred or athousand or ten thousand, etc. Preferably, there are (other) constraintson the transformation (deformation), for example in order to avoidpathological deformations (for instance, all the voxels being shifted tothe same position by the transformation). These constraints include forexample the constraint that the transformation is regular, which forexample means that a Jacobian determinant calculated from a matrix ofthe deformation field (for example, the vector field) is larger thanzero, and also the constraint that the transformed (deformed) image isnot self-intersecting and for example that the transformed (deformed)image does not comprise faults and/or ruptures. The constraints includefor example the constraint that if a regular grid is transformedsimultaneously with the image and in a corresponding manner, the grid isnot allowed to interfold at any of its locations. The optimising problemis for example solved iteratively, for example by means of anoptimisation algorithm which is for example a first-order optimisationalgorithm, such as a gradient descent algorithm. Other examples ofoptimisation algorithms include optimisation algorithms which do not usederivations, such as the downhill simplex algorithm, or algorithms whichuse higher-order derivatives such as Newton-like algorithms. Theoptimisation algorithm preferably performs a local optimisation. Ifthere is a plurality of local optima, global algorithms such assimulated annealing or generic algorithms can be used. In the case oflinear optimisation problems, the simplex method can for instance beused.

In the steps of the optimisation algorithms, the voxels are for exampleshifted by a magnitude in a direction such that the degree of similarityis increased. This magnitude is preferably less than a predefined limit,for instance less than one tenth or one hundredth or one thousandth ofthe diameter of the image, and for example about equal to or less thanthe distance between neighbouring voxels. Large deformations can beimplemented, for example due to a high number of (iteration) steps.

The determined elastic fusion transformation can for example be used todetermine a degree of similarity (or similarity measure, see above)between the first and second datasets (first and second images). To thisend, the deviation between the elastic fusion transformation and anidentity transformation is determined. The degree of deviation can forinstance be calculated by determining the difference between thedeterminant of the elastic fusion transformation and the identitytransformation. The higher the deviation, the lower the similarity,hence the degree of deviation can be used to determine a measure ofsimilarity.

A measure of similarity can for example be determined on the basis of adetermined correlation between the first and second datasets.

Preferably, atlas data is acquired which describes (for example defines,more particularly represents and/or is) a general three-dimensionalshape of the anatomical body part. The atlas data therefore representsan atlas of the anatomical body part. An atlas typically consists of aplurality of generic models of objects, wherein the generic models ofthe objects together form a complex structure. For example, the atlasconstitutes a statistical model of a patient's body (for example, a partof the body) which has been generated from anatomic information gatheredfrom a plurality of human bodies, for example from medical image datacontaining images of such human bodies. In principle, the atlas datatherefore represents the result of a statistical analysis of suchmedical image data for a plurality of human bodies. This result can beoutput as an image—the atlas data therefore contains or is comparable tomedical image data. Such a comparison can be carried out for example byapplying an image fusion algorithm which conducts an image fusionbetween the atlas data and the medical image data. The result of thecomparison can be a measure of similarity between the atlas data and themedical image data. The atlas data comprises positional informationwhich can be matched (for example by applying an elastic or rigid imagefusion algorithm) for example to positional information contained inmedical image data so as to for example compare the atlas data to themedical image data in order to determine the position of anatomicalstructures in the medical image data which correspond to anatomicalstructures defined by the atlas data.

The human bodies, the anatomy of which serves as an input for generatingthe atlas data, advantageously share a common feature such as at leastone of gender, age, ethnicity, body measurements (e.g. size and/or mass)and pathologic state. The anatomic information describes for example theanatomy of the human bodies and is extracted for example from medicalimage information about the human bodies. The atlas of a femur, forexample, can comprise the head, the neck, the body, the greatertrochanter, the lesser trochanter and the lower extremity as objectswhich together make up the complete structure. The atlas of a brain, forexample, can comprise the telencephalon, the cerebellum, thediencephalon, the pons, the mesencephalon and the medulla as the objectswhich together make up the complex structure. One application of such anatlas is in the segmentation of medical images, in which the atlas ismatched to medical image data, and the image data are compared with thematched atlas in order to assign a point (a pixel or voxel) of the imagedata to an object of the matched atlas, thereby segmenting the imagedata into objects.

DESCRIPTION OF THE FIGURES

In the following, the invention is described with reference to theappended figures which represent a specific embodiment of the invention.The scope of the invention is however not limited to the specificfeatures disclosed in the context of the figures, wherein

FIG. 1 is a flow diagram showing the basic steps of the disclosed methodaccording to the first aspect;

FIG. 2 shows a directional DBS electrode with a directional marker;

FIG. 3 illustrates an embodiment of the disclosed method according tothe first aspect; and

FIG. 4 illustrates a specific approach to determining the rotationalorientation of the electrode from the two-dimensional medical images.

FIG. 1 is a flow diagram illustrating the basic steps of the disclosedmethod in accordance with the first aspect, which in the illustrativeexample of FIG. 1 starts with a step S1.1 of acquiring the rotationalimage data. In subsequent step S1.2, the rotational orientation data isdetermined. Step S1.3 then continues with acquiring the tomographicimage data, followed by step S1.4 which encompasses determining theelectrode orientation data on the basis of the data acquired anddetermined in preceding steps S1.1. to 1.3.

FIG. 2 shows a directional DBS electrode 1 (also called lead) comprisinga cylindrical and elongate body on which contacts 2 are disposed. Thecontacts 2 include directional contacts 8 which do not run along thewhole circumference of the base body but are designed to emit anelectric field only in a three-dimensional sector spanning less than360° degrees of the circumference. In the example of FIG. 2, thedirectional contacts 8 each cover at least substantially about 60° ofthe circumference and divided from one another by slits 7 which formspaces between the directional contacts 8. The spaces may be empty orfilled with non-conductive material, for example the material of whichthe body of the electrode 1 is made. The slits 7 run parallel to thelongitudinal axis of the body of the electrode 1 and therefore lie on ageneratrix of the cylinder forming the basic shape of the electrode 1.The electrode 1 also comprises an orientation marker 3 comprising amarker band having a first part 5 and a second part 4 and a markerwindow 6. The rotational orientation of the orientation marker isdefined as a vector pointing in a direction to the exterior of the bodyof the electrode 1 and oriented perpendicular to the surface of thecentre of the first part 5, i.e. having its base in a point lying in themirror plane of symmetry of the first part 1 in which also thelongitudinal axis of the body of the electrode lies. The marker band ismade of platinum (Pt) or at least of a material (such as an alloy).comprising platinum (Pt), and is more radiopaque than the marker window6. In one example, the marker band is also more radiopaque than the bodyof the electrode 1. The optimal two-dimensional medical image is aradiography in which the depiction (image appearance) of the first part5 is the thinnest, i.e. is defined by the smallest number of imageelements (such as pixels), among the two-dimensional medical images.

As shown in FIG. 3, the rotational image data may be acquired by imagingthe anatomical structure in the patient's body by using a C-arm x-rayapparatus. Then, the image depiction of the electrode 1 (lead) isextracted from the two-dimensional medical images (2D x-rayimages/radiographies), for example by applying a segmentation algorithmto the two-dimensional medical images. In the box in the lower left-handcorner of FIG. 3 the rightmost two-dimensional medical image is chosenas the optimal two-dimensional medical because it contains the thinnestdepiction of the first part 5 of the marker band. As indicated by thearrow in that box, the rotational orientation of the electrode 1 (andtherefore the orientation marker 3) is determined to lie in the imageplane of the rightmost two-dimensional medical image and point to thelower right of that image.

As also shown in FIG. 3, a 3D (three-dimensional) image corresponding tothe tomographic image data or the transformed appearance data isacquired. The tomographic image data may be generated either by CT orreconstruction of a 3D image from the 2D x-ray-images. Alternatively oradditionally, the 3D image may be acquired on the basis of an MRtomography which has been transformed into a CT appearance, therebygenerating the transformed appearance data which also is athree-dimensional image data set. The transformation of the MRtomography embodies the tomographic image data and is transformed intoCT grey values by acquiring multi-modal atlas data and conducting amatch between the atlas data and the MR tomography. The match is calleduniversal atlas match in FIG. 3. Based on the correspondence between atissue-dependent MR grey value scale and a tissue-dependent CT greyvalue scale contained in the atlas, a CT (computed x-ray tomography) issimulated from the MR tomography by replacing the grey values of the MRtomography (e.g. voxel-wise) with the grey values of a corresponding CTimage.

From the 3D image, digitally reconstructed radiographs (DRRs) areproduced. In one example, only on DRR is produced from the perspectivetowards the anatomical structure corresponding to the perspectiveassociated with the optimal two-dimensional medical image. In anotherexample, DRRs are generated for all perspective for which atwo-dimensional medical image has been acquired or generated. Then, theDRR best matching the optimal two-dimensional medical image is selectedfor further processing. A transformation (called 2D-3D registration inFIG. 3) between the reference system of the 2D images and the DRR orDRRs is established, for example by fusing the image data sets to onanother. Based on that transformation, the rotational orientation of theelectrode can be determined in the reference system of the 2D x-rayimages based on knowledge of the imaging perspective relative to theanatomical structure associated with (i.e. used when) generating the 2Dx-ray images. The rotational orientation can then be transformed fromthe reference system of the 2D x-ray images into the reference system ofthe DRR or DRRs by applying the 2D-3D registration. Based on theknowledge of the imaging perspective used for generating the DRR orDRRs, the rotational orientation of the electrode can then be determinedin the reference system of the 3D image, as shown in the upper half ofFIG. 4. The rotational orientation thus determined can then be comparedfor example to a predetermined (e.g. desired) rotational orientation ofthe electrode, for example in the reference system of the 3D image. Ifthe determined rotational orientation is at least within a predetermineddistance substantially equal to the predetermined rotationalorientation, the envisaged medical procedure may start as desired. Ifthe determined rotational orientation is not at least within apredetermined distance substantially equal to the predeterminedrotational orientation, the rotational orientation of the electrode maybe adjusted until agreement with the predetermined rotationalorientation is found.

As shown in FIG. 4, the slits 7 between directional contacts 8 may beused for supporting determination of the rotational orientation, forexample to verify the result received from analyzing the two-dimensionalmedical images with regard to the image appearance of the orientationmarker. The right part of FIG. 4 illustrates that if an x-ray used forgenerating the two-dimensional medical image may with a finiteprobability pass through two slits 7 and thus generate a correspondingmark in the two-dimensional image because the material of which thedirectional contacts 8 are made is differs in radio-opacity from thematerial of which the slits 7 are made or with which they may be filled.For example, an x-ray passing through two slits 7 may produce a markindicating translucence compared to the image appearance of thedirectional contacts 8. Thereby, an additional indication may bereceived with an accuracy of about 60° in the example of FIGS. 1 and 4whether the rotational orientation determined from the image appearanceof the orientation maker is valid or not.

The disclosed method may further be summarized as follows.

The method uses images taken by an x-ray system while rotating around ananatomical structure such as the patient's head. A 3D (volumetric) imageof the head from any tomographic scanner may be used. Further, analgorithm is used for registering the 2D x-ray images to the 3D image.Another algorithm detects the lead(s) in the 2D x-ray images and definesthe angle of the lead's orientation marker with respect to the imageplane (i.e. with respect to the reference system of the 2D x-rayimages). The angle information is mapped back from 2D image space into3D image (anatomy) space by means of the registration. The computersystem is able to show a simulated projection of the 3D image blended onany of the 2D x ray images modulo the calculated registration in orderto allow the user for a quick check of registration precision.

Several embodiments are considerable:

-   -   Work with one x-ray, two x-ray or multiple (rotational) x-rays.        The more images are used, the more robust is the determination        of the angle    -   Use standard CT as a 3D image. They are calibrated to Hounsfield        values. Digitally reconstructed radiographs (DRR) can be        calculated from scratch.    -   Use reconstructed CT directly from the x-Ray scanner as 3D        image. Then no additional scan is necessary. Recalibration to HU        values may be necessary and can be done with help of Universal        Atlas    -   Use pre-operative MRI as a 3D image. Then this needs to be        preprocessed and transformed into Hounsfield values of a        corresponding CT representation. This can be done with help of        the Universal Atlas.    -   The calculation of the digitally reconstructed radiographs        (DRRs) can be done on graphics card.    -   The directional lead has slits between the segmented contacts        which are visible in x-rays at certain angles. These can be used        additionally in order to improve angle precision.    -   Leads can be either segmented by an algorithm in the x-rays or        in the 3D image.    -   Marker orientation can be found by template matching or by        machine learning.    -   Camera parameters (such as the imaging perspective) of the 2D        x-ray images may be taken from DICOM information stored        together/associated with the x-ray image information.    -   If not available from DICOM, camera parameters of X-Rays are        estimated e.g. from lead geometry in 2D images.

Aside from the rotational orientation, also the lead type may bedetected in x-rays (manufacturer, model), for example based oncomparison of the image appearance of at least part of the electrode(such as the orientation marker) with the electrode template data.

The disclosed method aims for a quick and traceable transfer ofinformation on DBS lead orientation from 2D images into 3D anatomy. Itis quick because the system contains an automatic algorithm which allowsfor registering 2D and 3D coordinates which otherwise would be acumbersome step needed to be done by the user manually (i.e. manualadoption of several degrees of freedom like shift/rotation/zoom/focuslength in order to match 2D and 3D images). Furthermore, the 2D-3Dregistration makes the final angle assignment traceable for the user. Hecan immediately check that the calculated angle makes sense in relationto both 2D and 3D image.

The invention claimed is:
 1. A computer-implemented method fordetermining an orientation of an electrode, the electrode beingconfigured for electrically stimulating an anatomical structure of apatient and comprising a rotational orientation marker, the methodcomprising executing, on at least one processor of at least onecomputer, steps of: acquiring, by the at least one processor, rotationalimage data describing two-dimensional medical images of the anatomicalstructure and the electrode, the two-dimensional medical images havingbeen taken with a two-dimensional medical imaging apparatus duringrotation of the medical imaging apparatus relative to the anatomicalstructure, the rotational image data further describing, for each of thetwo-dimensional medical images, an imaging perspective relative to theanatomical structure associated with the respective two-dimensionalmedical image and including at least two different imaging perspectivesobtained during rotation of the medical imaging apparatus relative tothe anatomical structure; wherein in a cross section of the electrodetaken perpendicular to a longitudinal axis of the electrode, the atleast two directional contacts form ring segments with one or more lessradio-opaque portions disposed in between the at least two directionalcontacts; wherein the at least two imaging perspectives are definedrelative to the anatomical structure by an x-ray passing through the oneor more less-radio-opaque portions to produce a mark indicatingtranslucence compared to an image appearance of the at least twodirectional contacts; determining, by the at least one processor andbased on the rotational image data, rotational orientation datadescribing the rotational orientation of the electrode in a referencesystem of the two-dimensional medical images; acquiring, by the at leastone processor, tomographic image data describing a set of tomographicmedical images of the anatomical structure, the tomographic image datarepresenting previously acquired three dimensional medical imagesrepresenting the anatomical structure in a three dimensional referencesystem; and, determining, by the at least one processor and based on therotational image data and the tomographic image data and the rotationalorientation data, electrode orientation data describing a rotationalorientation of the electrode in the three dimensional reference systemof the tomographic image data.
 2. The method according to claim 1,further comprising: acquiring, by the at least one processor,predetermined orientation data describing a predetermined rotationalorientation of the electrode in the reference system of thetwo-dimensional medical images; determining, based on the rotationalorientation data and the predetermined orientation data, optimalorientation data describing the two-dimensional medical image associatedwith a rotational orientation of the electrode in the reference systemof the two-dimensional medical image fulfilling a predeterminedcondition in relation to the predetermined rotational orientation, thetwo-dimensional medical image herein forth being called the optimaltwo-dimensional medical image; determining, by the at least oneprocessor and based on the tomographic medical image data, projectedimage data describing a projected tomographic medical image generatedfrom the tomographic medical image data from the imaging perspectiveassociated with the optimal two-dimensional medical image; and,determining, by the at least one processor and based on the projectedimage data and the rotational image data, projected orientation datadescribing the rotational orientation of the electrode in the referencesystem of the projected medical image.
 3. The method according to claim2, wherein the electrode orientation data is determined, by the at leastone processor, based on the projected orientation data and the projectedimage data.
 4. The method according to claim 2, wherein the projectedimage data is determined for each of the imaging perspectives with whichthe series of two-dimensional medical images is associated, and theprojected image data describes a projected tomographic medical image foreach of the imaging perspectives, and wherein the projected orientationdata is determined based on the projected tomographic medical image bestmatching the optimal two-dimensional medical image, which match isdetermined by at least one of: comparing colour values between theoptimal two-dimensional medical image and the projected tomographicmedical images; applying a fusion algorithm to register the optimaltwo-dimensional medical image to each one of the projected tomographicmedical images and selecting, from the projected tomographic medicalimages and for determining the projected orientation data, only theprojected tomographic medical image associated with the best fusionresult.
 5. The method according to claim 1, wherein determining therotational orientation data includes determining, by the at least oneprocessor and based on the rotational image data, an image appearance ofthe rotational orientation marker, by at least one of: segmenting animage appearance of the electrode in each of the two-dimensional medicalimages; edge detection of constituents of the two-dimensional medicalimages; comparing the image appearance of the electrode in thetwo-dimensional medical images to previously acquired and predeterminedelectrode template data describing constructional data of the electrode.6. The method according to claim 1, wherein each two-dimensional medicalimage is associated with a different imaging perspective.
 7. The methodaccording to claim 2, wherein determining the projected medical imagedata includes determining a transformation between a reference system inwhich the rotational image data is defined and the reference system inwhich the tomographic image data is defined, and wherein determining theelectrode orientation data includes applying the transformation to therotational orientation described by the rotational orientation data. 8.The method according to claim 1, wherein the rotational image data andthe tomographic image data have been generated by application of anx-ray-based imaging modality.
 9. The method according to claim 1,wherein the rotational image data has been generated by application ofan x-ray-based imaging modality and the tomographic image data has beengenerated by applying an imaging modality not involving application ofx-rays.
 10. The method according to claim 2, further comprising:acquiring, by the at least one processor, atlas data describing a modelof the anatomical structure and information about an image appearance ofthe anatomical structure in the imaging modality including by applyingmagnetic resonance imaging or positron emission imaging (PET) or anultrasound imaging (sonography) or magnetic resonance diffusion tensorimaging (MR-DTI) and in an x-ray-based tomographic imaging modality,wherein the x-ray-based tomographic imaging modality is computed x-raytomography; determining, by the at least one processor and based on thetomographic image data and the atlas data, transformed appearance datadescribing an image appearance of the anatomical structure in thex-ray-based tomographic imaging modality; and, wherein the electrodeorientation data is determined further based on the transformedappearance data, the projected image data is determined further based onthe transformed appearance data.
 11. The method according to claim 10,wherein determining the transformed appearance data includes matchingthe atlas data with the tomographic image data.
 12. The method accordingto claim 2, wherein the projected medical image is a digitallyreconstructed radiograph.
 13. A non-transitory computer program which,when running on at least one processor of at least one computer causesthe at least one computer to perform the steps of: acquire, by the atleast one processor, rotational image data describing two-dimensionalmedical images of an anatomical structure and an electrode, thetwo-dimensional medical images having been taken with a two-dimensionalmedical imaging apparatus during rotation of the medical imagingapparatus relative to the anatomical structure, the rotational imagedata further describing, for each of the two-dimensional medical images,an imaging perspective relative to the anatomical structure associatedwith the respective two-dimensional medical image and including at leasttwo different imaging perspectives relative to the anatomical structureobtained during rotation of the medical imaging apparatus relative tothe anatomical structure; wherein in a cross section of the electrodetaken perpendicular to a longitudinal axis of the electrode, the atleast two directional contacts form ring segments with one or more lessradio-opaque portions disposed in between the at least two directionalcontacts; wherein the at least two imaging perspectives are definedrelative to the anatomical structure by an x-ray passing through the oneor more less radio-opaque portions to produce a mark indicatingtranslucence compared to an image appearance of the at least twodirectional contacts; determine, by the at least one processor and basedon the rotational image data, rotational orientation data describing therotational orientation of the electrode in a reference system of thetwo-dimensional medical images; acquire, by the at least one processor,tomographic image data describing a set of tomographic medical images ofthe anatomical structure, the tomographic image data representingpreviously acquired three dimensional medical images representing theanatomical structure in a three dimensional reference system; and,determine, by the at least one processor and based on the rotationalimage data and the tomographic image data and the rotational orientationdata, electrode orientation data describing a rotational orientation ofthe electrode in the three dimensional reference system of thetomographic image data.
 14. A medical system for determining anorientation of an electrode, the electrode being configured toelectrically stimulating an anatomical structure of a patient andcomprising a rotational orientation marker, the system having at leastone processor with associated memory, the memory having instructions forthe at least one processor to: acquire, by the at least one processor,rotational image data describing two-dimensional medical images of theanatomical structure and the electrode, the two-dimensional medicalimages having been taken with a two-dimensional medical imagingapparatus during rotation of the medical imaging apparatus relative tothe anatomical structure, wherein in a cross section of the electrodetaken perpendicular to a longitudinal axis of the electrode, the atleast two directional contacts form ring segments with one or more lessradio-opaque portions disposed in between the at least two directionalcontacts; wherein the at least two imaging perspectives are definedrelative to the anatomical structure by an x-ray passing through the oneor more less radio-opaque portions to produce a mark indicatingtranslucence compared to an image appearance of the at least twodirectional contacts; the rotational image data further describing, foreach of the two-dimensional medical images, an imaging perspectiverelative to the anatomical structure associated with the respectivetwo-dimensional medical image and including at least two differentimaging perspectives relative to the anatomical structure obtainedduring rotation of the medical imaging apparatus relative to theanatomical structure; determine, by the at least one processor and basedon the rotational image data, rotational orientation data describing therotational orientation of the electrode in a reference system of thetwo-dimensional medical images; acquire, by the at least one processor,tomographic image data describing a set of tomographic medical images ofthe anatomical structure, the tomographic image data representingpreviously acquired three dimensional medical images representing theanatomical structure in a three dimensional reference system; and,determine, by the at least one processor and based on the rotationalimage data and the tomographic image data and the rotational orientationdata, electrode orientation data describing a rotational orientation ofthe electrode in the three dimensional reference system of thetomographic image data.
 15. The system according to claim 14, furthercomprising the two-dimensional medical imaging apparatus, wherein thetwo-dimensional medical imaging apparatus is operably coupled to the atleast one processor for allowing the at least one processor to receive,from the two-dimensional medical imaging apparatus, at least oneelectronic signal corresponding to the rotational image data.